Identifying Executable Plans

Total Page:16

File Type:pdf, Size:1020Kb

Identifying Executable Plans Identifying executable plans Tania Bedrax-Weiss∗ Jeremy D. Frank Ari K. J´onssony Conor McGann∗ NASA Ames Research Center, MS 269-2 Moffett Field, CA 94035-1000, ftania,frank,jonsson,[email protected] Abstract AI solutions for planning and plan execution often use declarative models to describe the domain of interest. Generating plans for execution imposes a different set The planning system typically uses an abstract, long- of requirements on the planning process than those im- term model and the execution system typically uses a posed by planning alone. In highly unpredictable ex- ecution environments, a fully-grounded plan may be- concrete, short-term model. In most systems that deal come inconsistent frequently when the world fails to with planning and execution, the language used in the behave as expected. Intelligent execution permits mak- declarative model for planning is different than the lan- ing decisions when the most up-to-date information guage used in the execution model. This approach en- is available, ensuring fewer failures. Planning should forces a rigid separation between the planning model acknowledge the capabilities of the execution system, and the execution model. The execution system and the both to ensure robust execution in the face of uncer- planning system have to agree on the semantics of the tainty, which also relieves the planner of the burden plan, and having two separate models requires the sys- of making premature commitments. We present Plan tem designer to replicate the information contained in Identification Functions (PIFs), which formalize what the planning model in the execution model. Since much it means for a plan to be executable, and are used in conjunction with a complete model of system behavior of the knowledge may be shared between the planning to halt the planning process when an executable plan is and execution systems, this produces a model synchro- found. We describe the implementation of plan identifi- nization problem. Furthermore, if the execution system cation functions for a temporal, constraint-based plan- wants to relay information back to the planner, in this ner. This particular implementation allows the descrip- scenario, the information has to be translated. Not us- tion of many different plan identification functions. ing the same language may be detrimental because syn- chronization and translation may introduce errors and Introduction increase model engineering effort. If both the execution and planning systems have a Planning has been an important problem in Artifcial common language, then information from and to the Intelligence, but plan execution is a problem that AI executive can flow seamlessly. Furthermore, changes has often overlooked. In fairly simplistic and highly- in the planning model are then automatically propa- predictable environments, the planning system can gated to the execution model. In addition, it is easier hand a fully-grounded plan to the execution system and to modify the boundary between planning and execu- the execution system will be able to execute it flaw- tion systems in such systems. Even if a single model for lessly. However, in unpredictable environments, a fully planning and execution is not available, there are still grounded plan will often result in execution failures. good reasons for making it easy to vary the boundary Additionally, it is inefficient for the planning process between planning and execution systems using a single to commit to decisions in advance that are likely to be model of system behavior. Many candidate execution invalidated during execution. One way to avoid these systems may be available; identifying the right one re- problems is to have an intelligent execution system that quires a planning model that can be used with any one is able to “fill in the blanks" given a plan that is not of the possible execution systems. fully grounded. Intelligent execution may range in com- executable plan plexity from fairly simple computations to a process re- An is a plan that the execution sys- sembling full-blown planning. Depending on the char- tem can make any remaining decisions and then trans- acteristics of the execution environment, the best plan late the result into commands that can be sent to the to hand to the execution system will contain more or hardware with which the system is interacting. Based less commitment and information. on this notion, the \executability" of a plan depends di- rectly on the capabilities of the execution system. For 1QSS Group, Inc. a general model of system behavior, we would like to 2Research Institute for Advanced Computer Science specify which parts of that model describe the commit- ments that should be made by the execution system. Models of System Behavior In this paper we provide the formalism and implemen- The system model defines the set of possible states tation of Plan Identification Functions PIFs . These and actions, along with rules that specify allowed functions exactly characterize the executable plans in and forbidden relations between actions and states. a model that is shared between the planner and the The states and actions are defined by predicates like executive. Thus, they serve to separate the duties of pointingAt(object) and slewFromTo(obj1, obj2). planning by partitioning the planning problem into a We define a partial plan as a collection of temporal pred- set of commitments that are made in advance, and a icate statements, based on a given model. We assume set that are interleaved with plan execution. that the parameter set for each predicate doesn't have We will proceed by presenting a simple example to to be fully grounded. This notion naturally supports clarify some of these notions. more flexible planning paradigms such as those used in constraint-based planning systems. A Simple Example The rules in the system model specify, directly or To examine the issues involved in generating plans for indirectly, the conditions for a state or action being in execution, let us consider a simple spacecraft that can the plan: slew (i.e, turn to different orientations), take pictures, • which instantiations of state/action predicates are and download pictures to Earth. valid A plan request for this spacecraft might consist of a set of picture requests, and then a request for down- • for each action/state, what other states or actions loading some or all of these pictures to Earth. The must exist in the plan to support it planning process would generate an \executable plan" • the temporal and parametric relations between states that achieved those goals. The execution agent would and actions then execute the plan by thrusting to rotate the space- craft, activating camera components, and transmitting For example, a model for our simple spacecraft data. would state that the predicates include pointingAt, slewingFromTo, takePicture, download A traditional approach to this problem would be . Legal in- based on separating the planning from execution at stantiations of slewingFromTo are limited to those some specific level of abstraction. For example, the where the origin and destinations are not the same, and takePicture planning process might involve generating slew ac- instantiations are limited to objects and tions, orientation maintenance actions, picture-taking times where an overly bright object, like the sun, is not actions, and download actions. The complete plan, at in the frame. There are a number of relations between takePicture that level of abstraction, would then be executed by predicates in this model; for example, a breaking each high-level action down into specific com- must be done within a period where the spacecraft is mands that together perform the action. The slew ac- pointing at the object in question. This means that pointingAt tions, for example, would be broken down into engine there must be a predicate in the plan, and warmup, thruster firing, wait, opposite thruster firing, that furthermore, the appropriate pointingAt must takePicture and then stabilization. The sequence of execution com- have the same object value as the , must takePicture mands would have to fit within the time allocated to start no later than the and must end no the slew action. earlier than the takePicture. If the execution system is sophisticated, it could de- It should be noted that this core approach covers ba- termine how fast to slew, since the slewing rate is con- sic STRIPS-like descriptions, where states are preserved trolled by the time spent firing the engines at the start by the frame axioms and action definitions define state and end of the slew. Slower slew rates typically save changes. It also covers constraint-based approaches, fuel. The execution system might also be able to deter- with and without an explicit representation of time or mine when to start activities that have some temporal resources. Furthermore, in STRIPS, the initial state flexibility. Rather than waiting until the next action and goal statements are simply part of a partial plan start time, which is bound to be later rather than ear- that must be extended to include the actions necessary lier, to provide a safety margin, the execution system to go from the initial state to a goal state. Since both could determine that all earlier actions have been com- planning and execution use the same model, the plan is semantically meaningful to both the planner and the pleted, that the action in question can start as early as 1 a given time, and then start that action at that time. executive . In the Remote Agent Experiment (JMM+00; The rest of the paper is organized as follows. We MNP+98), the planning process built a partial plan first provide a formal definition of PIFs and character- where certain temporal decisions were left to the ex- ize some useful properties of PIFs . We then describe ecution engine.
Recommended publications
  • Three Architectural Models for Compiler-Controlled Speculative
    Three Architectural Mo dels for Compiler-Controlled Sp eculative Execution Pohua P. Chang Nancy J. Warter Scott A. Mahlke Wil liam Y. Chen Wen-mei W. Hwu Abstract To e ectively exploit instruction level parallelism, the compiler must move instructions across branches. When an instruction is moved ab ove a branch that it is control dep endent on, it is considered to b e sp eculatively executed since it is executed b efore it is known whether or not its result is needed. There are p otential hazards when sp eculatively executing instructions. If these hazards can b e eliminated, the compiler can more aggressively schedule the co de. The hazards of sp eculative execution are outlined in this pap er. Three architectural mo dels: re- stricted, general and b o osting, whichhave increasing amounts of supp ort for removing these hazards are discussed. The p erformance gained by each level of additional hardware supp ort is analyzed using the IMPACT C compiler which p erforms sup erblo ckscheduling for sup erscalar and sup erpip elined pro cessors. Index terms - Conditional branches, exception handling, sp eculative execution, static co de scheduling, sup erblo ck, sup erpip elining, sup erscalar. The authors are with the Center for Reliable and High-Performance Computing, University of Illinois, Urbana- Champaign, Illinoi s, 61801. 1 1 Intro duction For non-numeric programs, there is insucient instruction level parallelism available within a basic blo ck to exploit sup erscalar and sup erpip eli ned pro cessors [1][2][3]. Toschedule instructions b eyond the basic blo ck b oundary, instructions havetobemoved across conditional branches.
    [Show full text]
  • Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK
    1 From Start-ups to Scale-ups: Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK Abstract—This paper1 describes some of the challenges and research questions that target the most productive intersection opportunities when deploying static and dynamic analysis at we have yet witnessed: that between exciting, intellectually scale, drawing on the authors’ experience with the Infer and challenging science, and real-world deployment impact. Sapienz Technologies at Facebook, each of which started life as a research-led start-up that was subsequently deployed at scale, Many industrialists have perhaps tended to regard it unlikely impacting billions of people worldwide. that much academic work will prove relevant to their most The paper identifies open problems that have yet to receive pressing industrial concerns. On the other hand, it is not significant attention from the scientific community, yet which uncommon for academic and scientific researchers to believe have potential for profound real world impact, formulating these that most of the problems faced by industrialists are either as research questions that, we believe, are ripe for exploration and that would make excellent topics for research projects. boring, tedious or scientifically uninteresting. This sociological phenomenon has led to a great deal of miscommunication between the academic and industrial sectors. I. INTRODUCTION We hope that we can make a small contribution by focusing on the intersection of challenging and interesting scientific How do we transition research on static and dynamic problems with pressing industrial deployment needs. Our aim analysis techniques from the testing and verification research is to move the debate beyond relatively unhelpful observations communities to industrial practice? Many have asked this we have typically encountered in, for example, conference question, and others related to it.
    [Show full text]
  • A Parallel Program Execution Model Supporting Modular Software Construction
    A Parallel Program Execution Model Supporting Modular Software Construction Jack B. Dennis Laboratory for Computer Science Massachusetts Institute of Technology Cambridge, MA 02139 U.S.A. [email protected] Abstract as a guide for computer system design—follows from basic requirements for supporting modular software construction. A watershed is near in the architecture of computer sys- The fundamental theme of this paper is: tems. There is overwhelming demand for systems that sup- port a universal format for computer programs and software The architecture of computer systems should components so users may benefit from their use on a wide reflect the requirements of the structure of pro- variety of computing platforms. At present this demand is grams. The programming interface provided being met by commodity microprocessors together with stan- should address software engineering issues, in dard operating system interfaces. However, current systems particular, the ability to practice the modular do not offer a standard API (application program interface) construction of software. for parallel programming, and the popular interfaces for parallel computing violate essential principles of modular The positions taken in this presentation are contrary to or component-based software construction. Moreover, mi- much conventional wisdom, so I have included a ques- croprocessor architecture is reaching the limit of what can tion/answer dialog at appropriate places to highlight points be done usefully within the framework of superscalar and of debate. We start with a discussion of the nature and VLIW processor models. The next step is to put several purpose of a program execution model. Our Parallelism processors (or the equivalent) on a single chip.
    [Show full text]
  • Visual Representations of Executing Programs
    Visual Representations of Executing Programs Steven P. Reiss Department of Computer Science Brown University Providence, RI 02912-1910 401-863-7641, FAX: 401-863-7657 {spr}@cs.brown.edu Abstract Programmers have always been curious about what their programs are doing while it is exe- cuting, especially when the behavior is not what they are expecting. Since program execution is intricate and involved, visualization has long been used to provide the programmer with appro- priate insights into program execution. This paper looks at the evolution of on-line visual repre- sentations of executing programs, showing how they have moved from concrete representations of relatively small programs to abstract representations of larger systems. Based on this examina- tion, we describe the challenges implicit in future execution visualizations and methodologies that can meet these challenges. 1. Introduction An on-line visual representation of an executing program is a graphical display that provides information about what a program is doing as the program does it. Visualization is used to make the abstract notion of a computer executing a program concrete in the mind of the programmer. The concurrency of the visualization in con- junction with the execution lets the programmer correlate real time events (e.g., inputs, button presses, error messages, or unexpected delays) with the visualization, making the visualization more useful and meaningful. Visual representations of executing programs have several uses. First, they have traditionally been used for program understanding as can be seen from their use in most algorithm animation systems [37,52]. Second, in various forms they have been integrated into debuggers and used for debugging [2,31].
    [Show full text]
  • INTRODUCTION to .NET FRAMEWORK NET Framework .NET Framework Is a Complete Environment That Allows Developers to Develop, Run, An
    INTRODUCTION TO .NET FRAMEWORK NET Framework .NET Framework is a complete environment that allows developers to develop, run, and deploy the following applications: Console applications Windows Forms applications Windows Presentation Foundation (WPF) applications Web applications (ASP.NET applications) Web services Windows services Service-oriented applications using Windows Communication Foundation (WCF) Workflow-enabled applications using Windows Workflow Foundation (WF) .NET Framework also enables a developer to create sharable components to be used in distributed computing architecture. NET Framework supports the object-oriented programming model for multiple languages, such as Visual Basic, Visual C#, and Visual C++. NET Framework supports multiple programming languages in a manner that allows language interoperability. This implies that each language can use the code written in some other language. The main components of .NET Framework? The following are the key components of .NET Framework: .NET Framework Class Library Common Language Runtime Dynamic Language Runtimes (DLR) Application Domains Runtime Host Common Type System Metadata and Self-Describing Components Cross-Language Interoperability .NET Framework Security Profiling Side-by-Side Execution Microsoft Intermediate Language (MSIL) The .NET Framework is shipped with compilers of all .NET programming languages to develop programs. Each .NET compiler produces an intermediate code after compiling the source code. 1 The intermediate code is common for all languages and is understandable only to .NET environment. This intermediate code is known as MSIL. IL Intermediate Language is also known as MSIL (Microsoft Intermediate Language) or CIL (Common Intermediate Language). All .NET source code is compiled to IL. IL is then converted to machine code at the point where the software is installed, or at run-time by a Just-In-Time (JIT) compiler.
    [Show full text]
  • EXE: Automatically Generating Inputs of Death
    EXE: Automatically Generating Inputs of Death Cristian Cadar, Vijay Ganesh, Peter M. Pawlowski, David L. Dill, Dawson R. Engler Computer Systems Laboratory Stanford University Stanford, CA 94305, U.S.A {cristic, vganesh, piotrek, dill, engler} @cs.stanford.edu ABSTRACT 1. INTRODUCTION This paper presents EXE, an effective bug-finding tool that Attacker-exposed code is often a tangled mess of deeply- automatically generates inputs that crash real code. Instead nested conditionals, labyrinthine call chains, huge amounts of running code on manually or randomly constructed input, of code, and frequent, abusive use of casting and pointer EXE runs it on symbolic input initially allowed to be “any- operations. For safety, this code must exhaustively vet in- thing.” As checked code runs, EXE tracks the constraints put received directly from potential attackers (such as sys- on each symbolic (i.e., input-derived) memory location. If a tem call parameters, network packets, even data from USB statement uses a symbolic value, EXE does not run it, but sticks). However, attempting to guard against all possible instead adds it as an input-constraint; all other statements attacks adds significant code complexity and requires aware- run as usual. If code conditionally checks a symbolic ex- ness of subtle issues such as arithmetic and buffer overflow pression, EXE forks execution, constraining the expression conditions, which the historical record unequivocally shows to be true on the true branch and false on the other. Be- programmers reason about poorly. cause EXE reasons about all possible values on a path, it Currently, programmers check for such errors using a com- has much more power than a traditional runtime tool: (1) bination of code review, manual and random testing, dy- it can force execution down any feasible program path and namic tools, and static analysis.
    [Show full text]
  • Code Transformation and Analysis Using Clang and LLVM Static and Dynamic Analysis
    Code transformation and analysis using Clang and LLVM Static and Dynamic Analysis Hal Finkel1 and G´abor Horv´ath2 Computer Science Summer School 2017 1 Argonne National Laboratory 2 Ericsson and E¨otv¨osLor´adUniversity Table of contents 1. Introduction 2. Static Analysis with Clang 3. Instrumentation and More 1 Introduction Space of Techniques During this set of lectures we'll cover a space of techniques for the analysis and transformation of code using LLVM. Each of these techniques have overlapping areas of applicability: Static Analysis LLVM Instrumentation Source Transformation 2 Space of Techniques When to use source-to-source transformation: • When you need to use the instrumented code with multiple compilers. • When you intend for the instrumentation to become a permanent part of the code base. You'll end up being concerned with the textual formatting of the instrumentation if humans also need to maintain or enhance this same code. 3 Space of Techniques When to use Clang's static analysis: • When the analysis can be performed on an AST representation. • When you'd like to maintain a strong connection to the original source code. • When false negatives are acceptable (i.e. it is okay if you miss problems). https://clang-analyzer.llvm.org/ 4 Space of Techniques When to use IR instrumentation: • When the necessary conditions can be (or can only be) detected at runtime (often in conjunction with a specialized runtime library). • When you require stronger coverage guarantees than static analysis. • When you'd like to reduce the cost of the instrumentation by running optimizations before the instrumentation is inserted, after the instrumentation is inserted, or both.
    [Show full text]
  • The Trusted Execution Module: Commodity General-Purpose Trusted Computing
    The Trusted Execution Module: Commodity General-Purpose Trusted Computing Victor Costan, Luis F. G. Sarmenta, Marten van Dijk, and Srinivas Devadas MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, USA [email protected], {lfgs,marten,devadas}@mit.edu Abstract. This paper introduces the Trusted Execution Module (TEM); a high-level specification for a commodity chip that can execute user- supplied procedures in a trusted environment. The TEM is capable of se- curely executing partially-encrypted procedures/closures expressing ar- bitrary computation. These closures can be generated by any (potentially untrusted) party who knows the TEM’s public encryption key. Compared to a conventional smartcard, which is typically used by pre-programming a limited set of domain- or application- specific commands onto the smartcard, and compared to the Trusted Platform Module (TPM), which is limited to a fixed set of cryptographic functions that cannot be com- bined to provide general-purpose trusted computing, the TEM is sig- nificantly more flexible. Yet we present a working implementation us- ing existing inexpensive Javacard smartcards that does not require any export-restricted technology. The TEM’s design enables a new style of programming, which in turn enables new applications. We show that the TEM’s guarantees of secure execution enable exciting applications that include, but are not limited to, mobile agents, peer-to-peer multiplayer online games, and anonymous offline payments. 1 Introduction The Trusted Execution Module (TEM) is a Trusted Computing Base (TCB) de- signed for the low-resource environments of inexpensive commercially-available secure chips. The TEM can securely execute small computations expressed as partially-encrypted compiled closures.
    [Show full text]
  • Embedded System Tools Reference Manual (UG1043)
    Embedded System Tools Reference Manual UG1043 (v2016.3)(v2016.1) OctoberApril 06, 5, 2016 2016 Revision History The10/05/2016: following Released table shows with Vivado the revi Designsion history Suite 2016.3 for this wi thoutdocument. changes from 2016.1. Date Version Revision 04/06/2016 2016.1 Added information about the supported processors and compilers. Added references to Zynq® UltraScale+™ MPSoC related documentation. Embedded System Tools Reference Manual www.xilinx.com Send Feedback 2 UG1043 (v2016.3)(v2016.1) October April 06, 5, 2016 2016 Table of Contents Revision History . 2 Chapter 1: Embedded System and Tools Architecture Overview Design Process Overview. 6 Vivado Design Suite Overview . 8 Software Development Kit . 9 Chapter 2: GNU Compiler Tools Overview . 12 Compiler Framework . 12 Common Compiler Usage and Options . 14 MicroBlaze Compiler Usage and Options. 29 ARM Cortex-A9 Compiler Usage and Options . 46 Other Notes . 48 Chapter 3: Xilinx System Debugger SDK System Debugger . 50 Xilinx System Debugger Command-Line Interface (XSDB) . 51 Chapter 4: Flash Memory Programming Overview . 52 Program Flash Utility . 53 Other Notes . 55 Appendix A: GNU Utilities General Purpose Utility for MicroBlaze Processors. 60 Utilities Specific to MicroBlaze Processors. 60 Other Programs and Files . 63 Appendix B: Additional Resources and Legal Notices Xilinx Resources . 64 Solution Centers. 64 Documentation Navigator and Design Hubs . 64 Embedded System Tools Reference Manual www.xilinx.com Send Feedback 3 UG1043 (v2016.3)(v2016.1) October April 06, 5, 2016 2016 References . 65 Training Resources. 65 Please Read: Important Legal Notices . 66 Embedded System Tools Reference Manual www.xilinx.com Send Feedback 4 UG1043 (v2016.3)(v2016.1) October April 06, 5, 2016 2016 Chapter 1 Embedded System and Tools Architecture Overview This guide describes the architecture of the embedded system tools and flows provided in the Xilinx® Vivado® Design Suite for developing systems based on the MicroBlaze™ embedded processor and the Cortex A9, A53 and R5 ARM processors.
    [Show full text]
  • Effective Compiler Support for Predicated Execution Using the Hyperblock
    Effective Compiler Support for Predicated Execution Using the Hyperblock Scott A. Mahlke David C. Lin’ William Y. Chen Richard E. Hank Roger A. Bringmann Center for Reliable and High-Performance Computing University of Illinois Urbana-Champaign, IL 61801 Abstract on the branch are then converted to predicated instructions dependent on the value of the corresponding predicate. In Predicated execution is an effective technique for dealing this manner, control dependences are converted to data de- with conditional branches in application programs. How- pendences in the code. If-conversion can eliminate all non- ever, there are several problems associated with conventional loop backward branches from a program. compiler support for predicated execution. First, all paths Predicated execution support has been used effectively for of control are combined into a single path regardless of their scheduling both numeric and non-numeric applications. For execution frequency and size with conventional if-conversion numeric code, overlapping the execution of multiple loop it- techniques. Second, speculative execution is difficult to com- erations using software pipeline scheduling can achieve high- bine with predicated execution. In this paper, we propose performance on superscalar and VLIW processors [4] [5] [6]. the use of a new structure, referred to as the hyperblock, With the abiity to remove branches with predicated exe- to overcome these problems. The hyperblock is an efficient cution support, more compact schedules and reduced code structure to utilize predicated execution for both compile- expansion are achieved with software pipelining. Software time optimization and scheduling. Preliminary experimen- pipelining taking advantage of predicated execution sup- tal results show that the hyperblock is highly effective for a port is productized in the Cydra 5 compiler [7] [8].
    [Show full text]
  • Symbolic Execution of Java Byte-Code
    Symbolic Execution of Java Byte-code Corina Pãsãreanu Perot Systems/NASA Ames Research ISSTA’08 paper: “Combining Unit-level Symbolic Execution and System-level Concrete Execution for Testing NASA Software” Corina Pãsãreanu, Peter Mehlitz, David Bushnell, Karen Gundy-Burlet, Michael Lowry (NASA Ames) Suzette Person (University of Nebraska, Lincoln) Mark Pape (NASA JSC) Automatic Test Input Generation • Objective: – Develop automated techniques for error detection in complex, flight control software for manned space missions • Solutions: – Model checking – automatic, exhaustive; suffers from scalability issues – Static analysis – automatic, scalable, exhaustive; reported errors may be spurious – Testing – reported errors are real; may miss errors; widely used • Our solution: Symbolic Java PathFinder (Symbolic JPF) – Symbolic execution with model checking and constraint solving for automatic test input generation – Generates test suites that obtain high coverage for flexible (user-definable) coverage metrics – During test generation process, checks for errors – Uses the analysis engine of the Ames JPF tool – Freely available at: http://javapathfinder.sourceforge.net (symbc extension) Symbolic JPF • Implements a non-standard interpreter of byte-codes – To enable JPF to perform symbolic analysis • Symbolic information: – Stored in attributes associated with the program data – Propagated dynamically during symbolic execution • Handles: – Mixed integer/real constraints – Complex Math functions – Pre-conditions, multithreading • Allows for mixed concrete and symbolic execution – Start symbolic execution at any point in the program and at any time during execution – Dynamic modification of execution semantics – Changing mid-stream from concrete to symbolic execution • Application: – Testing a prototype NASA flight software component – Found serious bug that resulted in design changes to the software Background: Model Checking vs.
    [Show full text]
  • Anti-Executable Standard User Guide 2 |
    | 1 Anti-Executable Standard User Guide 2 | Last modified: October, 2015 © 1999 - 2015 Faronics Corporation. All rights reserved. Faronics, Deep Freeze, Faronics Core Console, Faronics Anti-Executable, Faronics Device Filter, Faronics Power Save, Faronics Insight, Faronics System Profiler, and WINSelect are trademarks and/or registered trademarks of Faronics Corporation. All other company and product names are trademarks of their respective owners. Anti-Executable Standard User Guide | 3 Contents Preface . 5 Important Information. 6 About Faronics . 6 Product Documentation . 6 Technical Support . 7 Contact Information. 7 Definition of Terms . 8 Introduction . 10 Anti-Executable Overview . 11 About Anti-Executable . 11 Anti-Executable Editions. 11 System Requirements . 12 Anti-Executable Licensing . 13 Installing Anti-Executable . 15 Installation Overview. 16 Installing Anti-Executable Standard. 17 Accessing Anti-Executable Standard . 20 Using Anti-Executable . 21 Overview . 22 Configuring Anti-Executable . 23 Status Tab . 24 Verifying Product Information . 24 Enabling Anti-Executable Protection. 24 Anti-Executable Maintenance Mode . 25 Execution Control List Tab . 26 Users Tab. 27 Adding an Anti-Executable Administrator or Trusted User . 27 Removing an Anti-Executable Administrator or Trusted User . 28 Enabling Anti-Executable Passwords . 29 Temporary Execution Mode Tab. 30 Activating or Deactivating Temporary Execution Mode . 30 Setup Tab . 32 Setting Event Logging in Anti-Executable . 32 Monitor DLL Execution . 32 Monitor JAR Execution . 32 Anti-Executable Stealth Functionality . 33 Compatibility Options. 33 Customizing Alerts. 34 Report Tab . 35 Uninstalling Anti-Executable . 37 Uninstalling Anti-Executable Standard . 38 Anti-Executable Standard User Guide 4 | Contents Anti-Executable Standard User Guide |5 Preface Faronics Anti-Executable is a solution that ensures endpoint security by only permitting approved executables to run on a workstation or server.
    [Show full text]